Optimum design of single-sided linear induction motor using the neural networks and finite element method

Abstract

A new method for the optimal design of a single-sided linear induction motor (SLIM) is presented. The method utilizes the neural network and finite element method for optimizing the design parameters of SLIM. The finite element analysis is used to produce a variety of neural network training data and the neural network is used for optimizing the design parameters by sequential unconstrained minimization technique. As a result, it is shown that the novel method is very efficient and accurate as an optimization technique.